Category: Data Visitation
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Part 1: Reactive vs. Proactive: The High Cost of Unvalidated EHR Data
Electronic Health Records were meant to be the backbone of modern healthcare and AI clinical prediction system. Instead, the 2025 research landscape paints a sobering picture. EHR data is incomplete, inconsistent, and often wrong at a scale that threatens clinical research, AI development, and even day‑to‑day patient care. Across multiple new studies, a consistent theme…
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Data Visiting and the Future of Inclusive Biomedical Research
In the age of AI-driven discovery, biomedical research is undergoing a quiet revolution—one that’s not just about faster algorithms or bigger datasets, but about rethinking how we access and share data across borders, institutions, and communities. The Geographies of Trust report published on Zenodo offers a timely exploration of this shift, spotlighting technologies that respect…
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Data Visiting in Patient-Controlled Health Wallets
Back in 2019, we ran a project we called “Symphony” alongside three blockchain pioneers, driven by a bold vision: to empower patients with full control over their health data through a personal data wallet. The goal was to let individuals decide who could access their records — and even monetize that access if desired. We…
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FAIR Data Trains
The FAIR Data Train is a data analysis approach that combines two key elements: As described in the LIFES Networking Meeting from December 2024: The FAIR Data Train approach was introduced as a domain-agnostic system designed to enhance automated interoperability while adhering to FAIR principles. Key aspects include privacy-focused “data visiting”, foundational agreements for metadata…
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Federated Data Platforms vs. Data Visiting Technologies
What technologies and methods enable the access and analysis of sensitive data using AI/ML, while preserving data privacy and avoiding centralization? That’s the challenge federated data and data visitation technologies aim to solve. But are they the same thing? Not quite. This post will break down the key differences, explore their respective applications, and provide…
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Dataset Digital Twin in Biomedical Research
Imagine a holographic view of a patient—a Biomedical Digital Twin—reflecting their unique physiology, lifestyle, and medical history. This isn’t science fiction; it’s a rapidly evolving field transforming healthcare and research. This article explores various types of digital twins and their applications, with a focus on dataset digital twins. Types of digital twins in biomedical research…
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Part 1: Key Takeaways from the RDA Plenary on AI/ML and Interoperability
The 23rd RDA Plenary Meeting in San José, Costa Rica, brought together a global community of researchers to address the pressing issue of sustainable science. The plenary was divided into many sessions that ran simultaneously and were organized by RDA working groups (WGs) and interest groups (IGs). The event offered valuable insights and sparked innovative…